Genetic regulation of gene expression of MIF family members in lung tissue
Why this work is in the frame
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Bibliographic record
Abstract
Macrophage migration inhibitory factor (MIF) is a cytokine found to be associated with chronic obstructive pulmonary disease (COPD). However, there is no consensus on how MIF levels differ in COPD compared to control conditions and there are no reports on MIF expression in lung tissue. Here we studied gene expression of members of the MIF family MIF, D-Dopachrome Tautomerase (DDT) and DDT-like (DDTL) in a lung tissue dataset with 1087 subjects and identified single nucleotide polymorphisms (SNPs) regulating their gene expression. We found higher MIF and DDT expression in COPD patients compared to non-COPD subjects and found 71 SNPs significantly influencing gene expression of MIF and DDTL. Furthermore, the platform used to measure MIF (microarray or RNAseq) was found to influence the splice variants detected and subsequently the direction of the SNP effects on MIF expression. Among the SNPs found to regulate MIF expression, the major LD block identified was linked to rs5844572, a SNP previously found to be associated with lower diffusion capacity in COPD. This suggests that MIF may be contributing to the pathogenesis of COPD, as SNPs that influence MIF expression are also associated with symptoms of COPD. Our study shows that MIF levels are affected not only by disease but also by genetic diversity (i.e. SNPs). Since none of our significant eSNPs for MIF or DDTL have been described in GWAS for COPD or lung function, MIF expression in COPD patients is more likely a consequence of disease-related factors rather than a cause of the disease.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it